A Weighted Combination Evidence Method And Its Application In Trust Management

The research on uncertain information data processing come into focus in current artificial intelligence research field and evidence theory is very important method of uncertain information processing. Among the processing methods Dempster- Shafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. Dempster-Shafer theory does not require an assumption regarding the probability of the individual constituents of the set or interval. This is a potentially valuable tool for the evaluation of risk and reliability in engineering applications when it is not possible to obtain a precise measurement from experiments. An important aspect of this theory is the combination of evidence obtained from multiple sources. Based on a classic Dempster-Shafer's evidence theory, some concepts such as self-conflict and weighted evidence were defined. The aim of this paper focuses on the classic robust questions of the D-S theory. Further the weighted method is built to describe credit degree of evidence from different source and the method is compared with the related works. Finally, this paper build a Multi-Agent trust management model, which enriches matter of trust management and makes use of Dempster-Shafer theory. And at the same time the model is also application of evidence theory to some degree.